Drugs modulating stochastic gene expression affect the erythroid differentiation process

Abstract

To better understand the mechanisms behind cells decision-making to differentiate, we assessed the influence of stochastic gene expression (SGE) modulation on the erythroid differentiation process. It has been suggested that stochastic gene expression has a role in cell fate decision-making which is revealed by single-cell analyses but studies dedicated to demonstrate the consistency of this link are still lacking. Recent observations showed that SGE significantly increased during differentiation and a few showed that an increase of the level of SGE is accompanied by an increase in the differentiation process. However, a consistent relation in both increasing and decreasing directions has never been shown in the same cellular system. Such demonstration would require to be able to experimentally manipulate simultaneously the level of SGE and cell differentiation in order to observe if cell behavior matches with the current theory. We identified three drugs that modulate SGE in primary erythroid progenitor cells. Both Artemisinin and Indomethacin decreased SGE and reduced the amount of differentiated cells. On the contrary, a third component called MB-3 simultaneously increased the level of SGE and the amount of differentiated cells. We then used a dynamical modelling approach which confirmed that differentiation rates were indeed affected by the drug treatment. Using single-cell analysis and modeling tools, we provide experimental evidence that, in a physiologically relevant cellular system, SGE is linked to differentiation.

Universality of cell differentiation trajectories revealed by a reconstruction of transcriptional uncertainty landscapes from single-cell transcriptomic data

“…In the analysis of iPSCs differentiation into cardiomyocytes 35 , the key genes regulating cardiomyocyte differentiation are among the largest contributors to the overall transcriptional uncertainty at or around the peak in the landscape, supporting the idea that dynamic cell-to-cell variability has a functional role in cell-fate decision making processes 21,57,58 . Such an idea would be in congruence with the recent demonstration that, in a physiologically relevant cellular system, gene expression variability is functionally linked to differentiation 57,58 .…”

Uncertainty in cell fate decision making: Lessons from potential landscapes of bifurcation systems

“…All together, these results suggest that the change in entropy across cell differentiation depends of the type of the transition (single-fate or multi-fate) and is sensitive to the noise levels [34]. Our analysis, taken together with experimental observations, suggests that a much more nuanced consideration of the potential differentiation dynamics and noise may be advisable.…”

Investigating higher-order interactions in single-cell data with scHOT

“…From a biological perspective, the concept of characterizing coordinated changes over time could enable better characterization of the molecular processes underpinning cell fate choice. In particular, it will help us to better understand whether increased plasticity, as manifested by increased cell-to-cell variability, is a general feature that precedes all instances of cell fate commitment, or whether this is restricted to a specific set of early biological differentiation events in systems such as embryonic hepatoblast differentiation as found here, and other systems 7 , 45 – 50 . Such heterogeneity could also be a driver of differential cell fate or cell function in a spatial context: specific patterns of local correlation could indicate that a specific region of a tissue or organ is primed towards a specific fate.…”